Lot release and stability testing of biologics are essential parts of the quality control strategy for ensuring therapeutic material dosed to patients is safe and efficacious, and consistent with previous clinical and toxicological experience. Characterization of protein aggregation is of particular significance, as aggregates may lose the intrinsic pharmaceutical properties as well as engage with the immune system instigating undesirable downstream immunogenicity. While important, real-time identification and quantification of subvisible particles in the monoclonal antibody (mAb) drug products remains inaccessible with existing techniques due to limitations in measurement time, sensitivity or experimental conditions. Here, owing to its exquisite molecular specificity, non-perturbative nature and lack of sample preparation requirements, we propose label-free Raman spectroscopy in conjunction with multivariate analysis as a solution to this unmet need. By leveraging subtle, but consistent, differences in vibrational modes of the biologics, we have developed a support vector machine-based regression model that provides fast, accurate prediction for a wide range of protein aggregations. Moreover, in blinded experiments, the model shows the ability to precisely differentiate between aggregation levels in mAb like product samples pre- and post-isothermal incubation, where an increase in aggregate levels was experimentally determined. In addition to offering fresh insights into mAb like product-specific aggregation mechanisms that can improve engineering of new protein therapeutics, our results highlight the potential of Raman spectroscopy as an in-line analytical tool for monitoring protein particle formation.